Background. The under-five child mortality (U5CM) rate is the most important sensitive indicator of the socioeconomic and health status of a community, and the overall development of a nation. Despite the world having made substantial progress in reducing child mortality since 1990, the global U5CM rate was 41 per 1 000 in 2016. The rate is higher in Ethiopia than in several other low-and middle-income countries. Objectives. To estimate the effects of socioeconomic and demographic factors on U5CM in Ethiopia. Methods. A community-based cross-sectional study was conducted on 10 641 under-five children. The 2016 Ethiopian Demographic and Health Survey data were used for this research. Binary logistic regression was employed to identify factors affecting the U5CM rate. Results. The U5CM rate was 60 deaths per 1 000 live births. Children who were delivered at home (adjusted odds ratio (aOR) 1.30; 95% CI 1.04-1.63) and male (aOR 1.36; 95% CI 1.15-1.60) were at an increased risk of death. Children whose family size was between 1 and 3 (aOR 5.54; 95% CI 4.08-7.54), and 4 and 6 (aOR 1.94; 95% CI 1.55-2.43) were more likely to die before age 5 than those whose family size was ≥6. First-born (aOR 0.49; 95% CI 0.36-0.67), second-or third-born (aOR 0.51; 95% CI 0.39-0.67) and fourth-or fifth-born (aOR 0.71; 95% CI 0.56-0.91) children were less likely to die than those who were sixth-born and above. Similarly, singleton children (aOR 0.20; 95% CI 0.15-0.28), children residing in urban communities (aOR 0.55; 95% CI 0.40-0.76) and children whose families had protected sources of water (aOR 0.84; 95% CI 0.71-0.99) had reduced risks of death compared with their respective counterparts. Conclusions. The present study identified risk factors for under-five mortality in Ethiopia. Programmes to reduce under-five mortality in Ethiopia must focus on the place of delivery, households with unprotected sources of drinking water and families residing in rural areas.

Road traffic crashes are a major socio-economic and public health problem, affecting all people of the world and Ethiopia is a country with a very large number of traffic crashes and fatality rate. This study has major objective of assessing the predictors of road traffic accident in Bahir Dar city, Ethiopia and identifies factors that contribute to the occurrence of road traffic crashes that leads human death. Data regarding to the number of deaths per road traffic crash were obtained from Bahir Dar city administration traffic police office for a two year period from July 2015-June 2017. In this study we applied six count models namely Poisson, negative binomial, generalized Poisson, zero inflated Poisson, zero-inflated negative binomial and zero inflated generalized Poisson regression models. Based on different models comparison criteria, e.g. AIC, log likelihood and Vuong test ZIGP regression model provides more appropriate fit to the number of human death per road traffic crashes data considered in this study. Sex, age, driving under alcohol, fatigue, not give priority, days of weeks, road condition, overloading, over speeding, and type of accident were found to be statistically significant predictors of human death due to road traffic crash.